MAB-RP: A Multi-Armed Bandit based workers selection scheme for accurate data collection in crowdsensing

Yuwei Lou, Jianheng Tang, Feijiang Han, Anfeng Liu, Neal N. Xiong, Shaobo Zhang, Tian Wang, Mianxiong Dong

Abstract: Highlights•A recognition and inference scheme for workers' reputations to distinguish the attributes of workers.•A novel scheme to calibrate workers' systematic bias, expanding the workers' selection group and improving the accuracy.•A learning-based approach to derive workers' preferences, considering the heterogeneity of tasks in MCS.•A new MAB-based framework for recruitment about the workers.